Research on Video-Based Human Action Behavior Recognition Algorithms

被引:0
|
作者
Si, Haifei [1 ,2 ]
Hu, Xingliu [1 ]
Wang, Yizhi [1 ]
机构
[1] Jinling Inst Technol, Coll Intelligent Sci & Control Engn, Nanjing 211169, Jiangsu, Peoples R China
[2] Harbin Engn Univ, Coll Automat, Harbin 150001, Heilongjiang, Peoples R China
基金
美国国家科学基金会;
关键词
D O I
10.1088/1755-1315/440/3/032142
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Human action recognition is an important part of intelligent video processing, which has high research value and broad application prospects. This paper takes the video monitoring of the elderly living alone as an example to recognize human behavior, and chooses the video of indoor background taken by a single camera as the research object. The background subtraction method is used to extract moving objects from video, and the extracted moving objects are pretreated. Then, according to the overall outline of the object or the obvious features of a part of the object, the motion features are obtained to understand and identify the movement of the monitored object, such as walking and falling. Experiments show that the proposed algorithm has better processing effect for actual video.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] A survey of video-based human action recognition in team sports
    Yin, Hongwei
    Sinnott, Richard O.
    Jayaputera, Glenn T.
    ARTIFICIAL INTELLIGENCE REVIEW, 2024, 57 (11)
  • [2] Video-Based Abnormal Human Behavior Recognition-A Review
    Popoola, Oluwatoyin P.
    Wang, Kejun
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2012, 42 (06): : 865 - 878
  • [3] Video-Based Human Action Recognition Using Kernel Relevance Analysis
    Fernandez-Ramirez, Jorge
    Alvarez-Meza, Andres
    Orozco-Gutierrez, Alvaro
    ADVANCES IN VISUAL COMPUTING, ISVC 2018, 2018, 11241 : 116 - 125
  • [4] Video-based cattle identification and action recognition
    Chuong Nguyen
    Wang, Dadong
    Von Richter, Karl
    Valencia, Philip
    Alvarenga, Flavio A. P.
    Bishop-Hurley, Gregory
    2021 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA 2021), 2021, : 441 - 445
  • [5] Sensor Substitution for Video-based Action Recognition
    Rupprecht, Christian
    Lea, Colin
    Tombari, Federico
    Navab, Nassir
    Hager, Gregory D.
    2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), 2016, : 5230 - 5237
  • [6] Video-Based Temporal Enhanced Action Recognition
    Zhang H.
    Fu D.
    Zhou K.
    Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2020, 33 (10): : 951 - 958
  • [7] Video-based human posture recognition
    Herrero-Jaraba, E
    Orrite-Uruñuela, C
    Monzón, F
    Buldain, D
    CIHSPS 2004: PROCEEDINGS OF THE 2004 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR HOMELAND SECURITY AND PERSONAL SAFETY, 2004, : 19 - 22
  • [8] A review of video-based pig behavior recognition
    Yang, Qiumei
    Xiao, Deqin
    APPLIED ANIMAL BEHAVIOUR SCIENCE, 2020, 233
  • [9] Research on Video-based Traffic Sign Recognition
    Sun, Yuge
    Li, Lei
    Ye, Ning
    Zhao, Lihong
    Lei, Hongwei
    Yang, Jie
    Sheng, Weihua
    2017 IEEE 7TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2017, : 1500 - 1505
  • [10] FlowerAction: a federated deep learning framework for video-based human action recognition
    Thi Quynh Khanh Dinh
    Thanh-Hai Tran
    Trung-Kien Tran
    Thi-Lan Le
    Journal of Ambient Intelligence and Humanized Computing, 2025, 16 (2) : 459 - 470